《李宏毅深度学习教程》(李宏毅老师推荐👍),PDF下载地址:https://github.com/datawhalechina/leedl-tutorial/releases
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Updated
Jul 11, 2024 - Jupyter Notebook
《李宏毅深度学习教程》(李宏毅老师推荐👍),PDF下载地址:https://github.com/datawhalechina/leedl-tutorial/releases
Neural Network Distiller by Intel AI Lab: a Python package for neural network compression research. https://intellabs.github.io/distiller
micronet, a model compression and deploy lib. compression: 1、quantization: quantization-aware-training(QAT), High-Bit(>2b)(DoReFa/Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference)、Low-Bit(≤2b)/Ternary and Binary(TWN/BNN/XNOR-Net); post-training-quantization(PTQ), 8-bit(tensorrt); 2、 pruning: normal、reg…
AIMET is a library that provides advanced quantization and compression techniques for trained neural network models.
PaddleSlim is an open-source library for deep model compression and architecture search.
A curated list of neural network pruning resources.
A toolkit to optimize ML models for deployment for Keras and TensorFlow, including quantization and pruning.
[CVPR 2023] Towards Any Structural Pruning; LLMs / SAM / Diffusion / Transformers / YOLOv8 / CNNs
SOTA low-bit LLM quantization (INT8/FP8/INT4/FP4/NF4) & sparsity; leading model compression techniques on TensorFlow, PyTorch, and ONNX Runtime
OpenMMLab Model Compression Toolbox and Benchmark.
Neural Network Compression Framework for enhanced OpenVINO™ inference
PyTorch Implementation of [1611.06440] Pruning Convolutional Neural Networks for Resource Efficient Inference
Efficient computing methods developed by Huawei Noah's Ark Lab
Sparsity-aware deep learning inference runtime for CPUs
mobilev2-yolov5s剪枝、蒸馏,支持ncnn,tensorRT部署。ultra-light but better performence!
Embedded and mobile deep learning research resources
Libraries for applying sparsification recipes to neural networks with a few lines of code, enabling faster and smaller models
YOLO ModelCompression MultidatasetTraining
Tutorial notebooks for hls4ml
TinyNeuralNetwork is an efficient and easy-to-use deep learning model compression framework.
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